Dataset Information

Novel prognostic classification predicts overall survival of patients receiving salvage whole-brain radiotherapy for recurrent brain metastasis from breast cancer: A recursive partitioning analysis (KROG 16-12).

ABSTRACT:

Background

To investigate outcomes of salvage whole-brain radiotherapy (WBRT) for recurrent brain metastases (BM) from breast cancer (BC), to identify prognostic factors of overall survival (OS), and to propose a novel prognostic classification for OS in these patients.

Materials and methods

We identified 54 patients who had received salvage WBRT as the second brain-focused treatment for recurrent BM from BC (2000-2014). The median follow-up duration was 4.9 months. A recursive partitioning analysis (RPA) was conducted to develop a model to predict OS at the time of salvage WBRT.

Results

The median OS was 6.8 months. OS according to BC-specific graded prognostic assessment (breast-GPA), modified breast-GPA, and updated breast-GPA did not represent our cohort. In the multivariate analysis, a long time before salvage WBRT (≥16 months), control of primary BC or extracranial metastases, systemic treatment after salvage WBRT, and administration of a biologically effective dose for an α/β of 10 Gy (BED10) of salvage WBRT >37.5 Gy showed superior OS. We proposed three RPA classes based on the control of both primary BC and extracranial metastasis and BED10 of salvage WBRT: class I, class II, and class III. In this model, patients with class I experienced the best OS (34.6 months; class II, 5.0 months; class III, 2.4 months; P < 0.001).

Conclusions

In our RPA classification according to the control of both primary BC and extracranial metastasis and the dose of salvage WBRT, significant differences in OS were observed. The subsequent use of a systemic treatment showed better OS.

SUBMITTER: Kim JS

PROVIDER: S-EPMC8609050 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Novel prognostic classification predicts overall survival of patients receiving salvage whole-brain radiotherapy for recurrent brain metastasis from breast cancer: A recursive partitioning analysis (KROG 16-12).

Kim Jae Sik JS Kim Kyubo K Jung Wonguen W Shin Kyung Hwan KH Im Seock-Ah SA Kim Yong Bae YB Chang Jee Suk JS Choi Doo Ho DH Kim Haeyoung H Park Yeon Hee YH Kim Dae Yong DY Kim Tae Hyun TH Kwon Jeanny J Kang Ki Mun KM Chung Woong-Ki WK Kim Kyung Su KS Kim In Ah IA

Breast (Edinburgh, Scotland) 20211115

<h4>Background</h4>To investigate outcomes of salvage whole-brain radiotherapy (WBRT) for recurrent brain metastases (BM) from breast cancer (BC), to identify prognostic factors of overall survival (OS), and to propose a novel prognostic classification for OS in these patients.<h4>Materials and methods</h4>We identified 54 patients who had received salvage WBRT as the second brain-focused treatment for recurrent BM from BC (2000-2014). The median follow-up duration was 4.9 months. A recursive pa ...[more]

PMID: 34814043

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Project description:BackgroundChemoimmunotherapy is the first-line treatment of de novo metastatic nasopharyngeal carcinoma (dmNPC), with additional locoregional radiotherapy (LRRT) significantly prolonging patient survival. De novo metastatic nasopharyngeal carcinoma, however, demonstrates considerable heterogeneity, resulting in significant variability in patient outcomes. We developed and validated a prognostic tool for patients undergoing first-line chemoimmunotherapy plus LRRT and to evaluate the benefit of local therapy (LT) for distant metastases across different risk levels.Patients and methodsWe studied 364 dmNPC patients receiving initial platinum-based chemotherapy and anti-programmed cell death protein 1 immunotherapy followed by LRRT. Patients were randomly divided into training and validation cohorts (7 : 3 ratio). The primary endpoint was progression-free survival (PFS). A prognostic model for PFS was developed using recursive partitioning analysis (RPA).ResultsAn RPA model categorized patients into five prognostic groups based on number of metastatic lesions, liver metastasis status, and post-treatment Epstein-Barr virus DNA levels. Survival analysis identified three distinct risk groups. High-risk patients had significantly poorer PFS compared with medium- and low-risk groups (2-year PFS rate: training cohort: 13.7% versus 69.4% versus 94.4%, P < 0.001; validation cohort: 7.8% versus 65.1% versus 87.3%, P < 0.001). We investigated the impact of LT for distant metastases across these risk groups and found that only patients in the medium-risk group derived benefit from LT (2-year PFS rate: 77.5% versus 64.0%; hazard ratio = 0.535, 95% confidence interval 0.297-0.966, P = 0.035). Conversely, no survival benefit from LT for distant metastases was observed in the low-risk (P = 0.218) and high-risk subgroups (P = 0.793).ConclusionsOur RPA-based prognostic model integrates number of metastatic lesions, liver metastasis status, and post-treatment Epstein-Barr virus DNA levels to predict PFS in dmNPC patients undergoing chemoimmunotherapy plus LRRT. This model offers personalized treatment guidance, suggesting that patients in the medium-risk group may benefit from LT for distant metastases, while those in high- and low-risk groups may not.

Dataset Information

Novel prognostic classification predicts overall survival of patients receiving salvage whole-brain radiotherapy for recurrent brain metastasis from breast cancer: A recursive partitioning analysis (KROG 16-12).

Background

Materials and methods

Results

Conclusions

Publications

Novel prognostic classification predicts overall survival of patients receiving salvage whole-brain radiotherapy for recurrent brain metastasis from breast cancer: A recursive partitioning analysis (KROG 16-12).

Similar Datasets

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